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( 5 0 points ) ( 1 ) ( 5 points ) Consider a normalized floating point number system with beta = 1 0

(50 points)
(1)(5 points) Consider a normalized floating point number system with \beta =10(base), p =2, L =4
and U =4. Compute the underflow and overflow levels of the system, as well as its machine
precision. If you use Matlab, report your results up to 4 decimal digits.
(2) Consider the following matrix
A =
0.0011
11
.
(a)(10 points) Compute the LU factorization of A (without partial pivoting) by hand: A = L1U1.
(b)(5 points) Assume that the floating point system approximates numbers by rounding. Compute
the floating point approximation of L1 and U1 in the floating point system given in question (1)
and denote Le 1= fl(L1), Ue 1= fl(U1). Hint: the floating point approximation of an n \times n matrix
B, denoted Be , is defined such that Be (i, j)= fl(B(i, j)),1<= i, j <= n.
(c)(5 points) Compute Ae 1= Le 1Ue 1 and ||Ae 1 A||1/||A||1. If you use Matlab, report your results
up to 4 decimal digits.
(d)(10 points) Compute the LU factorization with partial pivoting of A by hand: P A = L2U2.
(e)(5 points) Assume that the floating point system approximates numbers by rounding. Compute
the floating point approximation of P , L2, U2 in the floating point system given in question (1)
and denote Pe = fl(P ), Le 2= fl(L2), Ue 2= fl(U2).
(f)(5 points) Compute Ae 2= Pe Le 2Ue 2 and ||Ae 2A||1/||A||1. If you use Matlab, report your results
up to 4 decimal digits.
(g)(5 points) Is LU factorization backward stable? Is LU factorization with partial pivoting backward stable?

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